Local field potentials in a pre-motor region predict learned vocal sequences
| Autor: | Adam Kadwory, Timothy Q. Gentner, Jairo Ismahar Chavez, Bradley Voytek, Vikash Gilja, Daril E. Brown, Derek Hung Nguyen, Ezequiel M. Arneodo |
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| Přispěvatelé: | Theunissen, Frédéric E |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Male
Computer science Anatomical structures Action Potentials Social Sciences Local field potential Mathematical Sciences Vocalization Database and Informatics Methods Multiple frequency Premovement neuronal activity Psychology Biology (General) education.field_of_study Grammar Ecology Animal Behavior Rehabilitation Motor Cortex Eukaryota Syllables Animal Models Biological Sciences Computational Theory and Mathematics Experimental Organism Systems Modeling and Simulation Neurological Vertebrates behavior and behavior mechanisms Sequence Analysis Research Article QH301-705.5 Bioinformatics Population Biology Phonology Research and Analysis Methods Basic Behavioral and Social Science Birds Cellular and Molecular Neuroscience Bursting Neural activity Sequence Motif Analysis Information and Computing Sciences Behavioral and Social Science Genetics Animals Speech education Molecular Biology Ecology Evolution Behavior and Systematics Zebra Finch Behavior Motor area Animal Neurosciences Organisms Motor control Biology and Life Sciences Linguistics Network dynamics Animal Communication nervous system Amniotes Animal Studies Finches Vocalization Animal Neuroscience Zoology |
| Zdroj: | PLoS Computational Biology PLoS Computational Biology, Vol 17, Iss 9, p e1008100 (2021) PLoS computational biology, vol 17, iss 9 |
| ISSN: | 1553-7358 1553-734X |
| Popis: | Neuronal activity within the premotor region HVC is tightly synchronized to, and crucial for, the articulate production of learned song in birds. Characterizations of this neural activity detail patterns of sequential bursting in small, carefully identified subsets of neurons in the HVC population. The dynamics of HVC are well described by these characterizations, but have not been verified beyond this scale of measurement. There is a rich history of using local field potentials (LFP) to extract information about behavior that extends beyond the contribution of individual cells. These signals have the advantage of being stable over longer periods of time, and they have been used to study and decode human speech and other complex motor behaviors. Here we characterize LFP signals presumptively from the HVC of freely behaving male zebra finches during song production to determine if population activity may yield similar insights into the mechanisms underlying complex motor-vocal behavior. Following an initial observation that structured changes in the LFP were distinct to all vocalizations during song, we show that it is possible to extract time-varying features from multiple frequency bands to decode the identity of specific vocalization elements (syllables) and to predict their temporal onsets within the motif. This demonstrates the utility of LFP for studying vocal behavior in songbirds. Surprisingly, the time frequency structure of HVC LFP is qualitatively similar to well-established oscillations found in both human and non-human mammalian motor areas. This physiological similarity, despite distinct anatomical structures, may give insight into common computational principles for learning and/or generating complex motor-vocal behaviors. Author summary Vocalizations, such as speech and song, are a motor process that requires the coordination of numerous muscle groups receiving instructions from specific brain regions. In songbirds, HVC is a premotor brain region required for singing; it is populated by a set of neurons that fire sparsely during song. How HVC enables song generation is not well understood. Here we describe network activity presumptively from HVC that precedes the initiation of each vocal element during singing. This network activity can be used to predict both the identity of each vocal element (syllable) and when it will occur during song. In addition, this network activity is similar to activity that has been documented in human, non-human primate, and mammalian premotor regions tied to muscle movements. These similarities add to a growing body of literature that finds parallels between songbirds and humans in respect to the motor control of vocal organs. Furthermore, given the similarities of the songbird and human motor-vocal systems, these results suggest that the songbird model could be leveraged to accelerate the development of clinically translatable speech prosthesis. |
| Databáze: | OpenAIRE |
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